US11191519B2 - Device, system, and method for hemispheric breast imaging - Google Patents

Device, system, and method for hemispheric breast imaging Download PDF

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US11191519B2
US11191519B2 US15/501,792 US201515501792A US11191519B2 US 11191519 B2 US11191519 B2 US 11191519B2 US 201515501792 A US201515501792 A US 201515501792A US 11191519 B2 US11191519 B2 US 11191519B2
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data
scattering
transducer
ultrasound
array
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US20170238898A1 (en
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Robert C. Waag
Jeffrey P. Astheimer
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Habico Inc
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Habico Inc
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/13—Tomography
    • A61B8/14—Echo-tomography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings
    • A61B8/0825—Detecting organic movements or changes, e.g. tumours, cysts, swellings for diagnosis of the breast, e.g. mammography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/13—Tomography
    • A61B8/15—Transmission-tomography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/40—Positioning of patients, e.g. means for holding or immobilising parts of the patient's body
    • A61B8/406—Positioning of patients, e.g. means for holding or immobilising parts of the patient's body using means for diagnosing suspended breasts
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/42—Details of probe positioning or probe attachment to the patient
    • A61B8/4272—Details of probe positioning or probe attachment to the patient involving the acoustic interface between the transducer and the tissue
    • A61B8/4281—Details of probe positioning or probe attachment to the patient involving the acoustic interface between the transducer and the tissue characterised by sound-transmitting media or devices for coupling the transducer to the tissue
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/44—Constructional features of the ultrasonic, sonic or infrasonic diagnostic device
    • A61B8/4483—Constructional features of the ultrasonic, sonic or infrasonic diagnostic device characterised by features of the ultrasound transducer
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/44—Constructional features of the ultrasonic, sonic or infrasonic diagnostic device
    • A61B8/4483—Constructional features of the ultrasonic, sonic or infrasonic diagnostic device characterised by features of the ultrasound transducer
    • A61B8/4494—Constructional features of the ultrasonic, sonic or infrasonic diagnostic device characterised by features of the ultrasound transducer characterised by the arrangement of the transducer elements
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/48—Diagnostic techniques
    • A61B8/483—Diagnostic techniques involving the acquisition of a 3D volume of data
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/5207—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of raw data to produce diagnostic data, e.g. for generating an image
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/5269—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving detection or reduction of artifacts
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/89—Sonar systems specially adapted for specific applications for mapping or imaging
    • G01S15/8906—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques
    • G01S15/8909—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques using a static transducer configuration
    • G01S15/8915—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques using a static transducer configuration using a transducer array
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/89—Sonar systems specially adapted for specific applications for mapping or imaging
    • G01S15/8906—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques
    • G01S15/8909—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques using a static transducer configuration
    • G01S15/8929—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques using a static transducer configuration using a three-dimensional transducer configuration
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/89—Sonar systems specially adapted for specific applications for mapping or imaging
    • G01S15/8906—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques
    • G01S15/8977—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques using special techniques for image reconstruction, e.g. FFT, geometrical transformations, spatial deconvolution, time deconvolution
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/89—Sonar systems specially adapted for specific applications for mapping or imaging
    • G01S15/8906—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques
    • G01S15/8993—Three dimensional imaging systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/89—Sonar systems specially adapted for specific applications for mapping or imaging
    • G01S15/8906—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques
    • G01S15/8959—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques using coded signals for correlation purposes

Definitions

  • breast cancer is a significant health problem worldwide. In the United States alone, more than 230,000 new cases of invasive breast cancer are estimated to be disposed each year and about 40,000 women are expected die of the disease this year. Globally, when excluding non-melanoma cancers of the skin, breast cancer is the most common cancer in women.
  • Imaging is the primary way that cancer in the breast can be detected when the cancer is small. In addition, imaging can also be used for staging and monitoring response to the treatment of a patient with breast cancer.
  • the breast can be imaged using a number of methods, including conventional x-ray mammography, x-ray tomosynthesis, and magnetic resonance imaging (MRI).
  • MRI magnetic resonance imaging
  • current implementations of these methods often suffer from low resolution, poor contrast, or other issues that reduce the effectiveness of these techniques in detecting or identifying breast disease.
  • X-ray mammography is generally considered to be the most cost-effective tool for the early detection of breast cancer.
  • specificity and positive predictive value of mammography is limited, due to the potential overlap is the appearances of benign and malignant lesions, and to poor contrast in patients with dense breast tissue.
  • Ultrasound is not typically used for the diagnosis of breast disease because the process of obtaining the images is highly operator dependent. Further, ultrasound resolution is generally not adequate, particularly in the direction orthogonal to the imaging plane, i.e., the slice thickness dimension, and speckle can make images hard to interpret or can obscure calcifications. Currant ultrasound techniques also often poorly describe lesion margins that are known to be an important feature for the diagnosis of cancer.
  • a device for volumetric ultrasound imaging includes an array of ultrasound transducer elements substantially configured in the shape of a hemisphere to form a cup-shaped volumetric imaging region within the cavity of the hemisphere.
  • the array of transducers includes 40 triangular planar facets.
  • 10 of the facets are equilateral triangles and 30 of the facets are isosceles triangles.
  • each triangular transducers includes 256 piezoelectric elements.
  • the piezoelectric elements are arranged pseudorandomly on each facet.
  • at least one of the transducers further includes a diverging lens.
  • at least one of the transducers further includes two matching layers.
  • the hemisphere array of transducers is positioned within the surface of a patient table, such that the opening of the cup-shaped volumetric imaging region is substantially flush with the patient table surface.
  • the device further includes a cup-shaped container sized to fit substantially within the imaging region cavity of the hemisphere.
  • the cup-shaped container is disposable.
  • a system for volumetric ultrasound imaging includes an array of planar faceted ultrasound transducers substantially configured in the shape of a hemisphere to form a cup-shaped volumetric imaging region within the cavity of the hemisphere, a plurality of data-acquisition assemblies connected to the transducers, and a network of processors connected to the data-acquisition assemblies.
  • the ultrasound transducers are configured to generate and receive ultrasound signals within the imaging region
  • the data-acquisition assemblies are configured to collect ultrasound signals received from the transducers and transmit measured data to the network of processors
  • the network of processors is configured to construct a volumetric image of as object within the imaging region based on the image data received from the data-acquisition assemblies.
  • the number of data-acquisition assemblies is equal to the number of transducer elements, and that each data-acquisition assembly is dedicated to an individual transducer.
  • the array of transducers comprises 40 triangular planar faceted transducer subarrays.
  • 10 of the facets are equilateral triangles and 30 of the facets are isosceles triangles.
  • each transducer comprises 256 piezoelectric elements.
  • each data-acquisition assembly comprises at least 256 send/receive channels.
  • the network of processors comprises at least 20 nodes.
  • each node comprises at least one graphical processing unit (GPU).
  • each node is configured to process data received from at least two data-acquisition assemblies in parallel.
  • a method for reconstructing a volumetric ultrasound image includes the steps of generating ultrasound signals from an array of transducer elements substantially arranged in the shape of a hemisphere, such that the generated signals are incident on a scattering object positioned within the cavity formed by the hemisphere of transducer elements; measuring a plurality of scattered ultrasound signals with the ultrasound transducer elements; pre-processing the measured signals with a plurality of data-acquisition assemblies; and reconstructing a volumetric image of the scattering object with a network of processors based on the pre-processed signals.
  • the image of the scattering object is reconstructed via an inverse-scattering model.
  • the image of the scattering object is reconstructed by relating the measured scattered ultrasound signals to background medium variation.
  • an estimate image of the scattering object is reconstructed from a subset of the measured signals; one or more refined images of the scattering object are reconstructed from the estimate image of the scattering object and pre-processed signals; and the volumetric image of the scattering object is reconstructed from the one or more refined images and pre-processed signals.
  • the background medium variation is substantially linear in relation to the measured signals.
  • the interpolation comprises a prefiltering step.
  • scattering measured in the hemisphere transducer array is used to estimate scattering object detail that would come from scattering in the antipodal hemisphere.
  • the measured signals are divided into overlapping subvolumes.
  • the subvolumes are tetrahedral.
  • the background medium variation of each subvolume is calculated independently.
  • the calculation of the background medium variation of each subvolume is processed substantially simultaneously.
  • an array of background medium variation values corresponding to the overlapping subvolumes is rotated during reconstruction.
  • the background medium variation array is rotated to align an axis of the background medium variation array with an axis of a portion of the transducer elements. In one embodiment, the rotation of the background medium variation array is factored into one or more skew operations.
  • virtual scattering measurements from the background medium variations are computed at the vertices of a regular grid that span the surface of each facet. In one embodiment, the virtual scattering measurement computations further comprise an inverse two-dimensional Fast Fourier transform of spatial frequency integrals. In one embodiment, the virtual scattering measurements are used to interpolate actual scattering measurements at the locations of the facet elements. In one embodiment, the interpolations further comprise a prefiltering step.
  • an estimate image of the scattering object is reconstructed from a subset of the measured signals; one or more refined images of the scattering object are reconstructed from the estimate image and pre-processed signals corresponding to the overlapping subvolumes of measured signals; and a volumetric image of the scattering object is reconstructed from the one or more refined images and pre-processed signals corresponding to the overlapping subvolumes of measured signals.
  • a time gate is applied to the measured signals prior to reconstruction to isolate the measured signals from different subvolumes.
  • FIG. 1 is a schematic of an exemplary embodiment of a hemispheric breast imaging system (HABIS) integrated with a patient examination table.
  • HBIS hemispheric breast imaging system
  • FIG. 2 is a schematic of another exemplary embodiment of a HABIS integrated with a patient examination table, wherein the examination table surface and a portion of the sides of the table have been removed.
  • FIG. 3 is a schematic of the front-end electronics of an exemplary embodiment of a HABIS, showing a hemispheric cup and ultrasound transducer assemblies.
  • FIG. 4 comprising FIGS. 4A through 4C is a set of images of an exemplary embodiment of a transducer element subassembly, which can form a part of a hemispheric ultrasound transducer array
  • FIG. 4A is a photo image of the inner surface of the transducer element subassembly
  • FIG. 4B is a cross-sectional X-ray image of a portion of the subassembly
  • FIG. 4C is a photo image of the outer surface of the subassembly.
  • FIG. 5 is a schematic of the front-end electronics of an exemplary embodiment of a HABIS, showing a portion of the data-acquisition subassemblies.
  • FIG. 6 is a schematic of the front-end electronics of an exemplary embodiment of a HABIS, showing a plurality of data-acquisition subassemblies connected to the ultrasound transducer assemblies.
  • FIG. 7 is a schematic of the front-end electronics of an exemplary embodiment of a HABIS, showing how an exemplary data-acquisition subassembly is connected to an ultrasound transducer assembly.
  • FIG. 8 is a schematic of the AC wiring and power supply distribution of an exemplary embodiment of a HABIS.
  • FIG. 9 is a schematic of the HABIS patient examination table of FIG. 1 positioned in an exemplary examination room.
  • FIG. 10 is a schematic of a hemispheric volume ( FIG. 10A ) and the tetrahedral region that is associated with a subtriangle of the hemispheric array ( FIG. 10B ).
  • the portion of the hemispheric volume imaged by the data from the triangular block of receive elements in the triangle is the tetrahedron formed by the vertices of the solid-line triangle and the center of the hemisphere.
  • FIG. 11A is a schematic of an exemplary embodiment of a high-performance computer network communicatively connected to the hemispheric transducer array of a HABIS.
  • FIG. 11B is an enlarged view of a portion of the high-performance computer network of FIG. 11A .
  • FIG. 12 is a diagram of a data processing flow through an exemplary HABIS and associated high-performance computer network.
  • FIG. 13 is a diagram of a tetrahedral region associated with a subtriangle of the hemispheric array. Image values are computed at vertices of a set of cubic subvolumes with centers that intersects the tetrahedral subvolume.
  • FIG. 14 is a diagram of the reconstruction of a 10-point resolution target ( 14 A) and a corresponding b-scan of the target ( 14 B).
  • the surfaces shown are 50% of the maximum amplitude.
  • the two upper-most points are 200 ⁇ m apart, the two left-most points are 300 ⁇ m apart, and the two right-most points are 400 ⁇ m apart.
  • an edge of the cubic volume has a length of 2.9 mm and the tic increment on the axes is 0.5 mm.
  • FIG. 15 is a set of images showing sections of a representative subvolume in a model of the breast.
  • Columns left to right Sections in the original subvolume, corresponding sections in the inverse-scattering reconstruction of the subvolume, and corresponding sections in the aberration-corrected b-scan of the subvolume.
  • an edge of the section has a length of 6.4 mm, and the outer region of the section is weighted by a window used to blend adjacent reconstructed subvolumes.
  • the x, y, and z axes are denoted accordingly.
  • the z axis is the polar axis of the hemisphere, the approximate direction of the b-scan lines which mainly highlight discontinuities perpendicular to them.
  • the original subvolume and the reconstructed subvolume are shown on a linear scale and the b-scan is shown on a log scale.
  • an element means one element or more than one element.
  • HBIS hemispheric array of ultrasound transducers and a computer network suitable for high-performance parallel processing of data collected from the hemispheric array.
  • a system may include software and associated algorithms to reconstruct volumetric images of a patient's breast. It is also contemplated herein that such a system can be configured to reconstruct volumetric images of other parts of a patient's anatomy, or any other scattering object.
  • patient refers to any animal amenable to the systems, devices, and methods described herein.
  • patient, subject or individual is a mammal, and more preferably, a human.
  • Ranges throughout this disclosure, various aspects can be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 2.7, 3, 4, 5, 5.3, and 6. This applies regardless of the breadth of the range.
  • a hemispheric breast imaging system that acquires ultrasound scattering measurements using a hemispheric array of transducers, and reconstructs the volume of a subject's breast using a high-performance computer network.
  • HABIS hemispheric breast imaging system
  • the data-acquisition apparatus includes an array of ultrasound transducers arranged in a generally hemispheric pattern and all electronics required for transmitting and receiving ultrasound signals from the array.
  • the high-performance computer network includes a plurality of interconnected computer nodes configured for fast, parallel processing of the data received from the data-acquisition apparatus.
  • Described herein is also an inverse scattering algorithm for reconstructing an image of a breast or other target scattering object.
  • the general purpose of the inverse scattering algorithm is to reconstruct an image of the scattering object from measurements of the effects that the object has on incident signals used to probe the object.
  • HABIS provides speckle-free, high-resolution, quantitative images of intrinsic tissue characteristics, e.g., sound speed and attenuation slope, for improved detection, diagnosis, and treatment monitoring of breast cancer.
  • the system can acquire data during an approximately two-second interval by using 10,240 parallel channels for transmission and reception.
  • the system can image an entire breast volume within minutes, with isotropic point resolution as good as the lateral resolution of x-ray mammography, by using an algorithm that independently and simultaneously reconstructs subvolumes spanning the breast.
  • ultrasound the system can be used to examine a breast with non-ionizing radiation for cancer detection.
  • the system overcomes limitations of x-ray mammography such as low resolution of contrast in dense breast tissue, i.e., breast tissue with high x-ray attenuation; distortion and discomfort resulting from compression-induced deformation of the breast, and poor imaging of breasts having implants. Accordingly, the system can significantly improve the detection and diagnosis of breast cancer, and can also improve the monitoring of response to breast cancer treatment, compared to systems currently available.
  • the reconstruction algorithm described herein can reconstruct subvolumes independently, i.e., in parallel.
  • Graphic processing units GPUs
  • HPCs high-performance computers
  • the system can include a GPU-based HPC network coupled to a data-acquisition apparatus that enables reconstructions of the breast volume to be obtained in a relatively short amount of time.
  • the breast volume can be reconstructed in less than 20 minutes, and in other embodiments. In less than 15 minutes, in less than 10 minutes, or in less than 5 minutes.
  • HABIS provides an improved and efficient way to screen for breast cancer and also to diagnose other breast diseases. In a manner previously unattainable.
  • HABIS comprises an apparatus for acquiring data from an array of ultrasound transducers.
  • HABIS includes an examination table that houses or otherwise integrates at least part or all of the data acquisition apparatus, which may include both its front-end and back-end electronics.
  • the data acquisition apparatus can be connected to a network of computers that can process or otherwise perform the desired image reconstruction.
  • the front-end electronics are arranged radially under the patient “head” end of the table around the generally hemispheric transducer array.
  • under the foot-end of the table are electronic modules that can include power supplies, power-supply filter boards, control boards, isolation transformers, high-voltage regulator boards, circuit breakers, and cable channels, as needed.
  • the system can also include other components suitable for use with a particular application associated with the image acquisition, such as a fluid-handling cart and an operator console which can be positioned near the examination table.
  • FIG. 1 an exemplary embodiment of the data acquisition apparatus 10 of the system is shown, wherein the apparatus is at least partially integrated into the surface of an examination table 20 generally having a surface 22 for a subject to lie on.
  • Surface 22 has an opening or cup 24 into which a scattering object, such as a patient's breast, can be placed.
  • the hemispheric transducer array of the system may form the exposed walls of cup 24 , or alternatively, cup 24 may be a permanent or disposable container that fits within the cavity of the transducer array hemisphere to prevent direct contact of the scattering object with the transducers, and/or to hold a suitable amount of coupling fluid, gel or other material used during the imaging procedure.
  • the container may be a detachable and disposable cup-shaped container. Accordingly, a patient can lie prone on table surface 22 with either the right breast or the left breast pendant in cup 24 . Further, cup 24 can be filled with a coupling fluid or any other suitable material as desired during an ultrasound imaging procedure.
  • FIG. 2 is a schematic of another embodiment of data acquisition apparatus 10 , wherein the examination table surface and a portion of the sides of table 20 have been removed. Again, the head end of table 20 houses the hemispheric array assembly, which is designed to image an object placed in cup 24 .
  • FIG. 3 is another schematic of data acquisition apparatus 10 , wherein all sides of table 20 have been removed to show a portion of a hemispherical army assembly 30 .
  • Hemispherical array assembly 30 includes a plurality of transducers, or transducer element assemblies 31 having an inner surface for transmitting and receiving ultrasound signals via a plurality of piezoelectric elements, and an outer surface configured with suitable circuitry for transferring electrical current and signal data to/from the piezoelectric elements within the transducer facets.
  • the inner surface of cup 24 forms a cavity for holding a scattering object, for example a patient's breast, that can be imaged using ultrasound.
  • cup 24 or otherwise the cavity formed by the inner surfaces of the transducers, also defines the imaging region within the apparatus or device.
  • the cup can comprise any material suitable for ultrasound analysis, as would be understood by a person skilled in the art.
  • the cup is substantially hemispherical in shape.
  • the cup may be a shape other than a hemisphere, provided that the array of ultrasound transducers and other electronic components of the system, and also the image reconstruction algorithm described later herein, are suitably modified to suitably image the resultant object volume within the imaging region.
  • hemispheric array assembly 30 comprises a plurality of data-acquisition subassemblies connected to the transducer elements. In one embodiment, hemispheric array assembly 30 comprises forty (40) data-acquisition subassemblies that are each connected to a single transducer element assembly. However, the number of data-acquisition subassemblies is not limited to forty, and can be more or less than forty, depending on the number of transducer assemblies and/or other factors, such as the desired resolution and/or speed of the reconstructed image.
  • FIG. 4A is a view of the inner surface of transducer element subassembly 31 comprising five triangular planar facets 32 .
  • Each planar facet 32 comprises a plurality of piezoelectric elements that are located underneath the dimples or depressions on the surface of facets 32 .
  • FIG. 4B a cross-sectional X-ray of an exemplary planar facet 32 is shown.
  • Facet 32 includes a surface layer 101 that comprises a plurality of depressions or dimples 102 .
  • a diverging lens is located in each dimple 102 .
  • surface layer 101 can be coated with a polymer, for example a Parylene polymer.
  • Beneath surface layer 101 are two matching layers 105 .
  • facet 32 can comprise a number of matching layers other than 2, for example 1 or 3 matching layers.
  • Matching layers 103 and 105 can comprise any material, and can be any thickness, that would be suitable for an ultrasound transducer matching layer, as would be understood by a person skilled in the art.
  • Beneath matching layers 103 and 105 is a plurality of ultrasound transducer elements 107 . Each transducer element 107 is substantially aligned with a dimple 102 .
  • Transducer elements 107 can comprise any material suitable for an ultrasound transducer known in the art, for example PZT crystal.
  • facet 32 comprises a backing layer (not shown) beneath transducer elements 107 .
  • the backing layer can comprise any suitable backing material for an ultrasound transducer.
  • the backing layer comprises a conductive epoxy.
  • facet 32 can comprise additional layers, for example a conductive metal coating on either side of the transducer elements, for grounding and excitation.
  • facet 32 can comprise additional components, for example printed circuit boards.
  • FIG. 4C is a view of the outer surface of transducer subassembly 31 . Five triangular planar facets 32 are connected together via a bracket 26 . A plurality of wire connectors 110 are located on the enter surface of each facet 32 . Wire connectors 110 can be used to communicatively couple transducer elements 107 to the data-acquisition components described later herein, for example via printed circuit boards.
  • transducer assemblies 31 of hemispheric array assembly 30 are shown coupled to forty front-end boards, i.e., data-acquisition subassemblies 33 (only a portion of these boards are shown in FIG. 5 ).
  • data-acquisition subassemblies 33 radiate from the axis of assembly 30 .
  • each data acquisition subassembly 33 comprises 256 channels of electronics, and is connected to the transducer assemblies 31 via cable connections 34 , which may be relatively short in length to minimize signal loss.
  • cable connections 34 are PCIe cables.
  • Hemispheric array assembly 30 also includes bottom-plane boards 35 for distributing power and timing, as would be understood by those skilled in the art.
  • data collected by at least one of the 256-channel data acquisition subassemblies 33 can be sent to imaging computers through suitable cables, e.g., PCIe cables.
  • the cables may be about five meters long, but is should be appreciated that these cables can be any length desired, as would be understood by a person skilled in the art.
  • This arrangement allows each ultrasound transducer element assembly 31 to be in close proximity with the front-end circuitry that is used to collect signals from the element. The close proximity between the transducer elements and the data acquisition circuitry lowers signal loss and extends the range and angle over which useful signals can be transmitted and received.
  • each data-acquisition subassembly 33 includes four blocks of 64-channel electronics positioned in successive angular sections of the board. This arrangement allows transducer assemblies 31 , comprising a total of 10,240 transducer elements, to be in proximity to the hemispheric array electronics. In such an embodiment, transducer assemblies 31 are connected to the electronics through 160 short cables.
  • FIG. 7 shows how the 256-channel data-acquisition subassemblies 33 plug into hemispheric array assembly 30 and shows the conical frame 39 that supports the inboard edge of the 256-channel subassemblies 33 .
  • Conical frame 39 also forms a plenum to direct air flow, for example air flow from fans that can be placed in another portion of the examination table.
  • each transducer element subassembly 31 includes a bracket 26 .
  • brackets 26 can be connected to data-acquisition subassemblies 33 via a plurality of flexible supports 27 .
  • transducer element assemblies 31 are connected to data-acquisition subassemblies 33 via wiring suitable for sending and receiving signals (not shown).
  • every data acquisition subassembly 33 receives 10,240 waveforms with 4,096 temporal samples in each waveform from 256 different transducer elements located in transducer assemblies 31 .
  • a total of 32.2 GB is acquired by each subassembly.
  • the data from all forty data acquisition subassemblies 33 i.e., a total of 40 ⁇ 32.2 GB, or 1.28 TB, would need to be aggregated and transferred to that system.
  • a significant part of the processing can be performed on data from each acquisition subassembly 33 without reference to data from the other acquisition subassemblies.
  • data acquisition apparatus 10 includes GPU cards that are distributed in the nodes of the data acquisition network. Further, superimposing a web of InfiniBand connections on the network enables rapid inter-node communication necessary in later stages of the computation so that the remainder of the reconstruction computations can be completed with similar speed.
  • the HABIS data-acquisition subassemblies each incorporate 256 channels of circuitry. Such an arrangement can be used to prevent noise from the digital electronics from interfering with analog reception.
  • FIG. 8 is a diagram showing the power supply assembly 40 positioned within the interior of table 20 .
  • Power supply assembly 40 can include components necessary for the operation of hemispheric array assembly 30 , including, but not limited to: a plurality of power supplies 41 , power-supply filter boards 42 , isolation transformers 44 , cooling fans 46 , air ducts 48 , high-voltage regulator boards, a power-control module, wiring connection blocks, disconnect switches, and circuit breakers within examination table 20 .
  • such components can be placed in a location outside of examination table 20 , for example in a secondary cabinet.
  • FIG. 9 is a diagram showing examination table 20 in an examination room.
  • Examination table 20 can be connected to an operator console 51 , which can be used to control any portion of the system, as needed.
  • a fluids cart 50 can be connected to table 20 to provide a supply and/or recirculation of coupling, i.e., ambient fluid to cup 24 .
  • table 20 can be connected to a computer network/scalable server set 70 for image reconstruction, as will be described later herein.
  • the components of HABIS can be connected to one or more power supplies suitable to provide power for their operation.
  • examination table 20 can be connected to a three-phase 208-volt AC supply through a disconnect switch and an isolation transformer.
  • Computer network 70 can be connected to another three-phase 208-volt AC supply through another disconnect switch.
  • no isolation transformer is included in computer network 70 because the only connection between examination table 20 and computer network 70 is a set of 40 low-voltage PCIe cables.
  • the various components of HABIS can be supplied power in any manner as would be understood by a person skilled in the art, and the power supply arrangement is not limited to the specific embodiments described herein.
  • HABIS is an integrated data-acquisition apparatus and high-performance network that rapidly collects imaging data and efficiently implements fast parallel computation of images via an inverse scattering algorithm.
  • the architecture of the system permits GPU-based parallel computations on each node and InfiniBand-based aggregation of results at each node.
  • the design of the system avoids extensive time-consuming data aggregation, permits parallel computation of refined data sets that substantially reduce the amount of data transferred between computer nodes for subsequent parallel reconstruction of subvolumes, and enables fast transfer of intermediate computational results between computing nodes.
  • the parallel computation takes place on two levels: a high level on each computing node and a low level on each GPU.
  • a head node in the network can provide command, control, and monitoring.
  • an Internet connection can enable command, control, and monitoring to be performed remotely.
  • Data-acquisition apparatus 10 provides a large number of independent channels, which can accommodate a large volume of data in a short time period, thereby exceeding the performance of currently available systems.
  • the system architecture may include separate connections between pairs of data-acquisition electronics sets and nodes of the high-performance computer-network. These connections allow processing to take place prior to aggregation of the receive signals.
  • the system architecture may also include configuration of individual compute nodes with cost-efficient resources that efficiently perform the parallel computations used in HABIS reconstructions.
  • the system architecture may also include InfiniBand connections and switching that efficiently perform in a cost-effective manner the burst transfers of data alter each stage of computation.
  • the system architecture may also include a mechanical configuration of the data-acquisition apparatus to minimize the lengths of the data paths between the transducer elements and the transmit and receive electronics so that the range and angle over which useful signals can be transmitted and received is greatly extended.
  • the system architecture may also include circuitry designs to reduce cost by consolidation of data-acquisition and data processing electronics. Further, the system architecture may also include a timing and control system that meets the stringent tolerances imposed by coherent imaging and transmission encoding.
  • the array of transducer elements of HABIS is arranged in a faceted construction to provide imaging of a generally hemispheric volume.
  • the hemispheric array in HABIS is approximated using 40 triangular planar facets.
  • ten of the facets are equilateral triangles and 30 of the facets are isosceles triangles.
  • the use of a faceted approximation of a hemisphere with two types of triangular planar elements greatly simplifies the construction of the array.
  • each facet contains 256 small diameter piezoelectric elements, as indicated by the dots on the facets in FIG. 10A , made from a ceramic material composite that suppresses undesirable lateral modes of vibration.
  • the elements on the facets are positioned pseudorandomly.
  • the pseudorandom positions permit the use of many fewer elements (and, thus, fewer independent transmit and receive channels) than would be otherwise required to avoid grating lobes during the formation of transmit and receive beams.
  • one configuration of pseudorandom positions is used on the equilateral facets and another configuration of positions is used on the isosceles facets. The use of two configuration sets of pseudorandom positions significantly facilitates practical fabrication of the array without degrading the capability of the array to form beams.
  • Each element may include a diverging lens that broadens the pattern of the transmit beam and the pattern of the receive sensitivity.
  • This broadening extends the volume, i.e., the solid angle, of the scattering object illuminated by transmissions from the elements.
  • the broadening also extends the volume i.e., the solid angle, of the scattering object from which ultrasound signals can be received by the elements.
  • the result of the extended coverage is an appreciably enhanced capability to concentrate focuses formed using the array.
  • Each element in the array may include two matching layers.
  • the matching layers produce a wider temporal-frequency bandwidth than would be obtained without the layers.
  • the matching layers also increase the transmission energy over the energy that would be transmitted without the layers.
  • the layers increase the sensitivity of reception over the reception sensitivity that would be obtained without the layers.
  • the transmit waveform applied to the transducer elements is designed to concentrate the transmitted energy within the temporal-frequency bandwidth of elements.
  • the receive circuitry contains a tuning element, i.e., an inductor, that cancels the bandwidth-narrowing effect of the capacitance associated with the transducer elements, the cable between the transducer element and the front-end electronics, the parasitic capacitance of the printed circuit wiring, and the input capacitance of the low-noise amplifier in the receiver chain.
  • a tuning element i.e., an inductor
  • the use of transmissions that are coded without degrading crosstalk and the ability to decode receptions without degrading crosstalk is enabled by the front-end electronics assembly design of HABIS.
  • the connection between the transducer elements and the cable to the electronics is made through a special signal redistribution arrangement implemented on a printed circuit board with wide trace separation and shielding. Additionally, a special pattern of shielded connections between the cable from the transducer and printed circuit board containing the front-end electronics reduces crosstalk significantly compared to the crosstalk that would otherwise exit.
  • the timing elements noted above are shielded and widely separated to suppress magnetic coupling between channels.
  • HABIS includes a high-performance computer network that is connected to the data-acquisition assembly.
  • a specialized architecture consisting of a data-acquisition apparatus and a high-performance computer network is required to collect the ultrasound data in a short time and to reconstruct the breast volume in minutes thereafter. This is because a computational capability must be integrated into HABIS to enable immediate parallel preprocessing of the acquired data.
  • the initial computations performed in the data-acquisition subassemblies yield refined data sets that substantially reduce the amount of data transferred between computer nodes for subsequent parallel reconstruction of subvolumes.
  • the system architecture may include 40 sets of data-acquisition subassemblies, with each set containing 256 independent transmit and receive channels, and 20 high-performance computing nodes with each node containing four GPUs.
  • comparable architectures with different numbers of data-acquisition subassemblies and high-performance computing nodes can be used, as the system is not limited to the specific numbers and arrangements of data-acquisition subassemblies and computer nodes described herein.
  • FIG. 11A is a diagram of an exemplary embodiment of a scalable computing network suitable to meet the processing needs for HABIS as described herein.
  • FIG. 11A shows the interconnections of a 21-node network that is comprised of 20 hybrid (acquisition and computation) nodes and a head (or control) node, which supervises the computing network.
  • the 40 data-acquisition boards are arranged in five groups of eight. Two data-acquisition boards are connected to each of the 20 computing nodes.
  • the head node may also serve as a console for rendering images and for controlling the instrument.
  • FIG. 11B shows a group of eight boards and their corresponding nodes in greater detail.
  • the 20 computing nodes, each with two GPUs, form an efficient numerical engine for massively parallel computations.
  • Single-precision GPUs are ideal computational engines for several reasons. Since the data acquired from the hemispheric transducer have 14 bits of precision, and since the computations applied to this data are not numerically unstable, single-precision arithmetic is sufficient, in fact, reduced memory requirements and faster transfer rates associated with single-precision data snake this format desirable. Each reconstruction requires a very large number (about 50 ⁇ 10 15 floating-point operations, i.e., 50 petaflops) of single-precision operations. Each node receives data from two of the 40 sets of data-acquisition electronics (shown as the green rectangles that contain four 64-channel blocks in FIG. 11B ) via fast PCIe connections.
  • InfiniBand connections to a central switch enable rapid inter-node communication necessary between stages of the computation. These switches allow 20 InfiniBand connections to be active simultaneously.
  • all the nodes of the network can also be connected to a local Ethernet switch (not shown) for command, control, and monitoring. A high-speed connection of the local Ethernet to the Internet further enables command, control, and monitoring from a remote location.
  • the reconstruction algorithm which is described in detail later herein, can be parallelized at both a high and a low level.
  • the high-level parallelization factors the computations into large-scale operations that are performed independently on separate nodes.
  • the low-level parallelization reduces these operations to a succession of vector and matrix computations that can be implemented as GPU kernels. Also, only a modest amount of logic is needed to direct the flow of data and to sequence the computations. Careful sequencing of these kernels can use the asynchronous data transfer capability of currently available general-purpose GPUs to eliminate data transfer latencies, resulting in improved efficiency. Data-transfer latencies are further suppressed by generation 3 PCIe connections used in currently available general-purpose GPUs.
  • each of the 40 sets of data-acquisition electronics subassemblies receives 10,240 waveforms from 256 different transducer elements.
  • FIG. 12 illustrates an exemplary data processing flow (via the image reconstruction algorithm) that permits processing to be performed in stages that consist of parallel computations on each node. As shown, these parallel computations on one node may be completely independent of the computations on the other nodes. As shown in FIG.
  • Stage I operations include preprocessing steps (such as time-variable gain compensation, transmission decoding, and application time gates to isolate the response from different regions), b-scan imaging, and initial approximation of the scattering object
  • Stage II operations include split-step propagation of fields that emanate front each of the 10,240 transducer elements and pass through the approximate scattering object, reduction of these fields to simplified representations each limited to a single subvolume, and estimation of the portions of the scattering measurements attributable to the approximate scattering object.
  • Stage III operations produce a refined approximation of the scattering object by using residual scattering measurements to reconstruct residual medium variations in each subvolume. After each stage of computations, the results of the computations at each node are redistributed to other nodes for the next stage of computations.
  • each HABIS compute node is equipped with four GPUs and a total of 128 GB of memory. These allocations allow each node to conduct four completely independent parallel computations during each processing stage. This combination of resources results in relatively low-cost compute nodes that have precisely the right kind of numerical capability for efficient implementation of the HABIS algorithm.
  • each HABIS compute node can include a different number of GPUs and/or memory, as would be understood by a person skilled in the art.
  • Each compute node in the architecture is responsible tor collecting a receive signal of 4,096 two-byte temporal samples from a group of 512 receive channels for each of 10,240 transmissions. Based on the previously-noted volume of data for a 256-channel set, the total volume of all these samples is about 43 GB. Excluding overhead, this volume of data can be transferred over a fast 16-lane PCIe connection with an overall transfer rate of 8 GB/s in about 5.4 seconds and can be transferred over a pair of such PCIe connections in about 2.7 seconds.
  • Preprocessing occurs initially in each node without internode communication and consists of transmit-receive channel response equalization, compensation for time-varying gain, Fourier transformation, and signal decoding requires expansion of the two-byte samples to a larger size.
  • HABIS although other expansions are possible, the expansion to a larger size is accomplished by conversion of the two-byte integer samples into four-byte floating-point values. This increases the volume of data associated with one node to 86 GB from 43 GB.
  • the required node-to-node transfers can be performed quickly using InfiniBand connections instead of PCIe connections.
  • the efficiency of InfiniBand connections is illustrated by considering the transfer of results from the parallel Stage II calculations, i.e., the scattering-measurement matrix ⁇ tilde over (M) ⁇ with entries ⁇ tilde over (M) ⁇ mn for the approximate scattering object.
  • This matrix is comprised 10,240 ⁇ 10,240 complex numbers that are each eight bytes.
  • the size of the entire matrix is about 9.84 GB, of which one-twentieth resides on each compute node.
  • the aggregation of the entire matrix at each node for the Stage III computations requires a total transfer of
  • this transfer can be completed in four seconds using a single InfiniBand connection, and can be completed in about 0.2 seconds using 20 simultaneously-active InfiniBand connections.
  • the preprocessing and b-scan imaging that take place in Stage I are performed with no communication between the 20 nodes in the network. However, full inverse scattering reconstruction is completed by the Stage II and Stage III computations that require node-to-node transfers of data over the InfiniBand network.
  • the 20 nodes also need to receive commands from an operator using a terminal to control the data collection, processing operations, b-scan image formation, and image reconstruction via inverse scattering.
  • Communication software provides the necessary capabilities for data exchange, distributed control, and coordinated calculations among the nodes.
  • Each of the 20 nodes includes a library that provides an interface to the other 19 nodes and a head node with a keyboard and monitor.
  • commands originated by an operator can be broadcast to the 20 computing nodes by using control program that runs on each node.
  • the program can include logic that allows each node to determine its data-acquisition functions from the operator-originated requests.
  • the program also supervises the preprocessing calculations. Additional programs that run on all the nodes form b-scan images and reconstruct images via inverse scattering.
  • the terminal that accepts operator commands can be used as a user interface that runs on one of the 20 nodes or, alternatively, on the head node.
  • Monochromatic, i.e., single-frequency, measurements of scattering measurements are used in the HABIS imaging algorithm.
  • the measurements are conveniently arranged as a two-dimensional matrix M of complex values with 10,240 rows and 10,240 columns.
  • the value of the matrix entry M nm with row index m and column index n is the scattering amplitude that is measured at the n-th receiving element in response to a transmission from the m-th element.
  • Scattering objects are reconstructed by determining variations of the background medium ⁇ (x) that account for the observed scattering measurements. This determination requires a mathematical model that relates the medium variations to the scattering measurements.
  • a weak-scattering model i.e., one in which the scattered wave is small relative to the incident wave, is desirable because the scattering measurements in a weak-scattering model depend linearly on the medium variations.
  • the explicit expression for weak scattering is M mn ⁇ n ( x ) ⁇ m ( x ) ⁇ ( x ) d 3 x Eq.
  • ⁇ m (x) denotes the spatially varying amplitude of the field that is transmitted by element m and propagates through an empty background
  • ⁇ n (x) denotes the spatially varying sensitivity pattern of receiver n that also propagates through an empty background.
  • the transmit field of element n is the same as the receive sensitivity pattern of element n.
  • weak scattering is usually not very accurate in practical applications because, in actual measurements, the value ⁇ m (x) of the transmit field that appears in the integrand of Eq. (1) is altered by medium variations encountered between the transmit element and x, and, likewise, the value ⁇ n (x) of the receiver sensitivity pattern that also appears in the integrand of Eq. (1) is altered by medium variations encountered between x and the receive element.
  • a more accurate model of the scattering measurements is formulated by incorporating an approximate scattering object in the scattering expression.
  • Equation (2) reduces to the original weak scattering expression given by Eq. (1) when an empty background is used for the approximate scattering object, but Eq. (2) is more accurate than Eq. (1) when the approximate object is a good approximation of the true object. For this reason, inverse scattering algorithms are usually iterative. In each iteration, the approximate scattering object ⁇ /(x) is improved by appending a refinement term ⁇ (x) that is derived from Eq. (2). This is the general framework for inverse scattering. The main differences between specific implementations are in the way that the refinements are estimated.
  • ⁇ tilde over ( ⁇ ) ⁇ n (x) and ⁇ tilde over ( ⁇ ) ⁇ m (x) are approximate oscillatory signals that do not take into account the influence of variations to the approximate object that are encountered as the fields propagate to x from the transmit element, and from x to the receive element. If these influences cause appreciable phase shifts in ⁇ tilde over ( ⁇ ) ⁇ n (x) and ⁇ tilde over ( ⁇ ) ⁇ m (x), then the scattering contribution that Eq. (2) attributes to ⁇ (x) will be weighted erroneously. Thus, Eq.
  • the HABIS imaging algorithm substitutes a two-step procedure for the general iterative scheme outlines above.
  • an approximate scattering object is estimated to obtain field approximations that are good enough to ensure that Eq. (2) is accurate in the region of interest.
  • a single inverse-scattering refinement is then computed to produce a sharper and more detailed reconstruction of the medium variations in this region.
  • Starting with a high-quality initial estimate can bypass many iterations in the early stage when convergence is slow.
  • the method used to obtain the initial approximation to the scattering object and the method used for iterative refinement of the scattering object are described in the sections below along with other important aspects of the HABIS imaging methodology.
  • ⁇ tilde over ( ⁇ ) ⁇ m (x) spatially varying amplitude of field transmitted from element m that propagates through ⁇ (x)
  • the typical strategy for estimation of ⁇ (x) is to adopt a finite-dimensional representation of ⁇ (x) that reduces Eq. (2) to a system of linear equations.
  • Some commonly used parameterizations of ⁇ (x) include: sample values at the vertices of a rectilinear grid, a linear combination of sine functions that are centered at the vertices of a rectilinear grid, or a linear combination of the eigen functions of a scattering operator.
  • the systems of equations that result from these parameterizations are usually either underdetermined or overdetermined and must be supplemented with auxiliary conditions, such as norm minimization, to ensure that the solution is unique and well-conditioned. In many cases, the numerical problems associated with solving these large systems of equations are significant.
  • ⁇ (x) at each location is assumed to depend linearly on the residual scattering measurements and may, therefore, be estimated by
  • ⁇ mn (x) is a matrix of coefficients that varies from point to point.
  • M mn ⁇ tilde over (M) ⁇ mn (x) that appears on the right side of Eq. (3).
  • K (x, x′) may be interpreted as the imaging kernel for the estimate
  • (x) Further improvement of (x) is realized by extending the set of usable spatial frequencies to a symmetric region that contains the original asymmetric region. The improvement is accomplished by using low-spatial-frequency components of (x) to model the relationship between the real and imaginary parts of ⁇ (x). This relationship, together with symmetry properties of the Fourier transform, can then be used to evaluate spatial-frequency components of ⁇ (x) at spatial frequencies that are antipodal to the spatial frequencies in the original asymmetric region. This results in the final estimate (x) of the ⁇ (x) that is used to add detail and resolution to the approximate scattering object
  • the HABIS procedure for estimating ⁇ (x) separates the overall estimate into estimates for each of the subvolumes that can be computed independently.
  • the computations are, therefore, ideally suited to high-level parallelization that assigns estimates of each subvolume to a different compute node of a high-performance computer network;
  • the estimate in each subvolume is found by direct computations (i.e., computations that are not directed by conditions that depend on results of prior computations) and that can be ‘vectorized,’ i.e., executed in parallel.
  • An initial approximation of the scattering object is found by imaging methods that are similar to b-scan algorithms used in currently available commercial ultrasound imaging systems. As noted in the preceding section, initial estimates with good accuracy are needed to eliminate slowly converging iterations. These estimates are developed from a scattering model that is similar to the weak scattering model of Eq. (1), but with an important difference.
  • the scattering measurements used to form the initial estimate are temporal responses to a pulse transmission while the scattering measurements represented by Eq. (1) are amplitudes of harmonic responses to monochromatic transmissions.
  • the medium variations are estimated in subvolumes that can be reconstructed in parallel.
  • the interior of the hemisphere is partitioned into tetrahedrons rather than cubes.
  • Bach tetrahedron has one vertex at the origin of the hemisphere, and three other vertices that form a subtriangle of one of the triangular facets of the hemispheric array.
  • FIG. 10 shows the tetrahedral regions that are associated with subtriangle A of the hemispheric array. Since the hemispheric array previously described herein consists of 40 facets and each facet is divided into four subtriangles, the interior of the hemisphere is partitioned into 160 tetrahedrons.
  • the medium variations in each tetrahedron are estimated from the scattered signals that are received by the 64 transducer elements contained in the subtriangle of the hemispheric array that forms the outer face of the tetrahedron. Since the data-acquisition apparatus transfers all the received signals from the elements in this subtriangle to the same compute node, the signals are automatically distributed in data sets that are suitable for this parallel computation. Each receive element collects a total of 10,240 signals.
  • ⁇ nm (x) denotes the geometric time delay ( ⁇ x ⁇ x m ⁇ + ⁇ x ⁇ x n ⁇ /c 0 . Since reflections can come from any illuminated inhomogeneity, the total reflected pressure detected at x n is given by
  • ⁇ mn ⁇ ( t ) ⁇ p ⁇ ( t - ⁇ nm ⁇ ( x ′ ) ) ⁇ x ′ - x m ⁇ ⁇ ⁇ x ′ - x n ⁇ ⁇ ⁇ ⁇ ( x ) ⁇ d 3 ⁇ x ′ .
  • Equation (10) is a representation of one temporal signal in the complete map of 10,240 ⁇ 10,240 element-to-element responses.
  • the strength of the reflector ⁇ (x) at location x in subtriangle A is estimated by forming the sum
  • ⁇ ⁇ ( x , t ) ⁇ [ ⁇ m ⁇ A ⁇ A 1 ⁇ A 2 ⁇ A 3 ⁇ ⁇ ⁇ n ⁇ A ⁇ ⁇ p ⁇ ( t + ⁇ nm ⁇ ( x ) - ⁇ nm ⁇ ( x ′ ) ) ] ⁇ ⁇ ⁇ ( x ′ ) ⁇ d 3 ⁇ x ′ .
  • ⁇ ⁇ ( x , 0 ) ⁇ [ ⁇ m ⁇ A ⁇ A 1 ⁇ A 2 ⁇ A 3 ⁇ ⁇ ⁇ n ⁇ A ⁇ ⁇ p ⁇ ( ⁇ nm ⁇ ( x ) - ⁇ nm ⁇ ( x ′ ) ) ] ⁇ ⁇ ⁇ ( x ′ ) ⁇ d 3 ⁇ x ′ Eq . ⁇ ( 13 ) that represents ⁇ (x, 0) as the imaged value of ⁇ (x) that results from the imaging kernel
  • Envelope detection entails demodulation, i.e., multiplication by e j ⁇ 0 t , where ⁇ 0 is the nominal center or carrier frequency of the pulse p (t), followed by a lowpass filter.
  • envelope detection is a nonlinear process that produces imaged values that do not map to mechanical properties of the medium.
  • the estimate ⁇ tilde over ( ⁇ ) ⁇ (x) is, therefore, only used to identify the structure of the scattering object.
  • Explicit values of the medium variations that are assigned to this structure are determined by other means.
  • the computations that assign values of sound speed and attenuation to the medium variations in subtriangle A make use of aberration estimates at a series locations x 1 A , x 2 A , . . . along the line from the center of the subtriangle to the center of the hemisphere (See FIG. 10 ). These aberration estimates are also used to compensate the receive signals in Eq. (11) to improve the accuracy of the estimate ⁇ tilde over ( ⁇ ) ⁇ (x) given by Eq. (15). Estimation of aberration is, therefore, a key step in this imaging procedure, and is described below.
  • the time delays of arrival times for reflections from x will have the form ⁇ nm ( x )+ ⁇ m ( x )+ ⁇ n ( x ) Eq. (19) where ⁇ m (x) and ⁇ n (x) are adjustments to the geometric delay ⁇ mn (x) that account for changes in sound speed between the transmitter at x m and x n and between x and the receive at x n . These terms cause misalignment of the time signals in the summation in Eq. (11) or, equivalently, phase variations in the frequency components that appear in the summation in Eq. (17).
  • ⁇ ( n ) ⁇ ( x , t ) ⁇ m ⁇ A ⁇ A 1 ⁇ A 2 ⁇ A 3 ⁇ ⁇ ⁇ x - x m ⁇ ⁇ ⁇ x - x n ⁇ ⁇ ⁇ mn ⁇ ( t + ⁇ nm ⁇ ( x ) ) ⁇ ⁇ and Eq .
  • ⁇ ( n ) ⁇ ( x , t ) ⁇ [ ⁇ m ⁇ A ⁇ A 1 ⁇ A 2 ⁇ A 3 ⁇ ⁇ p ⁇ ( t + ⁇ nm ⁇ ( x ) - ⁇ m ⁇ ( x ) + ⁇ n ⁇ ( x ) - ⁇ nm ⁇ ( x ′ ) ) ] ⁇ ⁇ ⁇ ( x ′ ) ⁇ d 3 ⁇ x ′ ⁇ ⁇ and Eq .
  • ⁇ ( 21 ⁇ a ) ⁇ ( n ′ ) ⁇ ( x , t ) ⁇ [ ⁇ m ⁇ A ⁇ A 1 ⁇ A 2 ⁇ A 3 ⁇ ⁇ p ⁇ ( t + ⁇ n ′ ⁇ m ⁇ ( x ) + ⁇ m ⁇ ( x ) + ⁇ n ′ ⁇ ( x ) - ⁇ n ′ ⁇ m ⁇ ( x ′ ) ] ⁇ ⁇ ⁇ ( x ′ ) ⁇ d 3 ⁇ x ′ .
  • ⁇ ( n ) ⁇ ( x , ⁇ ) ⁇ m ⁇ A ⁇ A 1 ⁇ A 2 ⁇ A 3 ⁇ ⁇ ⁇ x ′ - x m ⁇ ⁇ ⁇ x ′ - x n ⁇ ⁇ ⁇ mn ⁇ ( ⁇ ) ⁇ e - j ⁇ ⁇ ⁇ nm ⁇ ( x ) ⁇ ⁇ And Eq .
  • Estimates of the time shift differences for every pair of adjacent receive elements in triangular subdivisions can be summed along paths from the central element to form estimates ⁇ n (x) of the time shifts at each of the 64 receiving elements. These estimates can then be used to adjust the geometrically-determined phase shifts to compensate for aberration along the ray paths to the receiving elements. Range-dependent compensation for attenuation can be included by using amplitude factors along with the phase factors for time shift compensation on receive.
  • ⁇ ( m ) ⁇ ( x , ⁇ ) ⁇ n ⁇ A ⁇ ⁇ ⁇ x ′ - x m ⁇ ⁇ ⁇ x ′ - x n ⁇ ⁇ ⁇ mn ⁇ ( ⁇ ) ⁇ e - j ⁇ ⁇ ⁇ ⁇ [ ⁇ nm ⁇ ( x ) + s n ⁇ ( x ) ] ⁇ ⁇ and Eq .
  • the root-mean-square size of the aberration delays generally increases with depth. Also, estimates of the time delay differences between adjacent elements become inaccurate when the aberration is strong. Additional processing is then needed to detect and correct for circulation errors in the time delay differences or to form intermediate estimates of delay differences between adjacent clusters of elements. These complications are avoided by evolving the aberration delays along the line from the center of the triangle of receive elements to the origin of the hemisphere.
  • initial aberration estimates at x 1 A are formed at a depth that is shallow enough to insure that the aberration is weak.
  • the aberration at x 2 A will be stronger.
  • the aberration at x 2 A can be computed using geometric delays that are already compensated by the estimated aberration at x 1 A . Thus, at each step, only the incremental aberration is estimated.
  • a focus of this approach is to implement aberration correction as a straightforward computation that does not require conditional logic.
  • Image values are computed as magnitudes of complex envelopes given by Eq. (15). These computations use compensated geometric delays given by Eq. (27) with aberration adjustments that are most appropriate for the imaged location, i.e., adjustments that are estimated from the focus x k A that is closest to the image point. However, the image values are not evaluated along scan lines as is usually the case. Instead, the image values are computed at the points where the vertices of a fixed three-dimensional grid intersect the tetrahedron formed by the triangle of receive elements and the center of the hemisphere as shown in FIG. 13 . These image values are reported to the head compute node that consolidates the estimated medium variations from all 160 tetrahedral subvolumes into a single three-dimensional array. This arrangement permits rapid reconstruction of a breast volume that can be rendered by standard three-dimensional rendering software.
  • the medium variations that are produced by the procedure described above consist of intensities that are similar to the pixel intensities of b-scan images. To obtain an initial approximation of the scattering object these imaged intensities must be translated into the tissue mechanical properties of sound speed and attenuation. Sound speed assignments are more critical because variations in sound speed determine the phase distortion of the fields ⁇ tilde over ( ⁇ ) ⁇ n (x) and ⁇ tilde over ( ⁇ ) ⁇ m (x).
  • the first step is to segment the intensity variations into regions with similar amplitude and speckle characteristics.
  • the methods used for this segmentation can be tailored to the specific characteristics of the imaged intensities, as would be understood by a person skilled in the art. Further, the methods can be based on methods developed for segmenting MRI images of breast tissue that are currently known in the art. For example, a comparison of temporal and spectral scattering methods using acoustically large breast models derived from magnetic resonance images is provided in Hesford et al., 2014, J. Acoust. Soc. Am., 136 (2).
  • the segmentation may yield a decomposition of the medium into a small number (e.g., 10 to 20) of disjoint regions 1 , 2 , . . . . These regions are assumed to represent tissues that have the unknown sound speeds c 1 , c 2 , . . . .
  • b-scan images are usually formed by synthetic focusing of the received signals along a scan line (or at least a segment of a scan line) that is aligned with one axis of the image.
  • a scan line or at least a segment of a scan line
  • the resolution realized by the HABIS algorithm is better because separate transmit and receive focuses are formed at each voxel.
  • Efficiency is realized in the HABIS algorithm by imaging tetrahedral subvolumes in parallel. They also differ in the schema for using progressive compensations that are based on estimates from focal points of increasing depth.
  • Propagation of monochromatic fields through the approximate scattering object is a time consuming computation that is required by the reconstruction procedure.
  • Multipole or k-space methods may be used to obtain these fields, but these algorithms are too computationally costly to propagate fields from all 10,240 transducer elements.
  • the split-step algorithm is able to perform these propagations more efficiently.
  • Split-step methods separate monochromatic waves into components that travel in forward and backward directions with respect to a distinguished z axis. If the backward traveling components are ignored, then the propagation can proceed in steps that derive field values on successive x-y planes from the field values on preceding planes.
  • exact forward propagators for these steps are nonlinear combinations of spatial and frequency domain operators that do not commute.
  • these propagators must be approximated by alternating sequences of operators that act in the spatial domain and the spatial-frequency domain.
  • the propagators are approximated as a product of a single spatial-domain operator and a single frequency-domain operator.
  • these propagators are only accurate when the propagated fields are limited to spatial frequencies with small transverse components. Better approximations that include additional terms are often called wide-angle approximations because they are applicable to fields that have spatial frequencies with larger transverse components.
  • Exact forward propagators are exponential operators of the form exp[jk 0 ⁇ z( ⁇ square root over (1+P+Q) ⁇ 1)], where Q is a multiplication operator in spatial coordinates and P is a multiplication operator in spatial-frequency coordinates. If the P and Q operators only produce small variations, then a first-order binomial expansion of the radical can be used to obtain the approximate propagator exp [jk 0 ⁇ z(P+Q)/2]. Further approximation of the exponential gives either exp(jk 0 ⁇ zP/2) exp(jk 0 ⁇ zQ/2) or exp(jk 0 ⁇ zQ/2) exp(jk 0 ⁇ zP/2).
  • split-step perturbations In addition to wide-angle correction, a perturbation form of the split-step algorithm can be derived that gives substantially more accuracy than simple split-step propagation without requiring any additional FFTs. Although the method may not be as accurate as propagations that include the wide-angle correction, much better results than narrow-angle propagators can be: obtained with essentially no additional cost.
  • Another computation that the HABIS reconstruction procedure requires is the evaluation of the scattering measurements ⁇ tilde over (M) ⁇ mn that are due to the approximate scattering object. These measurements are deducted from the actual scattering measurements M mn to obtain the residual measurements M mn ⁇ tilde over (M) ⁇ mn that are used to determine the refinement ⁇ (x).
  • a much more efficient method for evaluating Eq. (29) has been developed.
  • the method is based on: 1) Expression of the integral in the spatial-frequency domain; 2) Expansion of the Fourier transform of ⁇ n (x) as an angular spectrum to reduce the three-dimensional spatial-frequency integral to a surface integral over a sphere of spatial frequencies; 3) Interpolation of spatial-frequency components on the sphere to values on hemispheres that are parameterized by two-dimensional grids with the same planar orientations as the facets; 4) Evaluation of scattering measurements on two-dimensional spatial grids that each contain one of the array facets by taking the inverse two-dimensional Fourier transforms of the spatial-frequency arrays obtained in Step 3 ; and 5) Interpolation of the values on regular arrays of scattering measurements to obtain the values of scattering measurements at the locations of the pseudo-random distribution of element positions.
  • the array of medium variations that prescribe the scattering object must be rotated so that one dimension of the array is aligned with the element axis.
  • the medium variations must be rotated to 40 different orientations that are determined by the 40 facets of the hemispheric array (because the facet normal is the propagation axis of every element in a facet).
  • the split-step propagations produce three-dimensional arrays of field values at the same grid locations as the rotated medium variations, and these arrays must be further rotated to a single common orientation to facilitate subsequent computations.
  • GPU algorithms are most efficient when memory accesses are coalesced and are transferred to and from global memory as infrequently as possible.
  • the algorithm can factor three-dimensional rotations into a series of skew operations that interpolate shifted values along one of the three dimensions of the array.
  • Such a rotation algorithm can be several times faster than conventional algorithms rotations, and can also provide increased precision more efficiently than conventional algorithms. Further description of such rotation algorithms as contemplated herein are provided in Appendix A.
  • the algorithm for computing scattering measurements and the algorithm for rotating three-dimensional arrays described above both require interpolation of a set of data values at the vertices of a regularly sampled grid. A large number of interpolated values are generally required. However, in some cases the interpolated locations are spaced irregularly, while in other cases they occur at regular intervals, e.g., at the midpoints of the sample intervals in the original array.
  • each interpolated value is computed as a linear combination of sample values in the original array
  • the computational cost of each interpolation is roughly proportional to the number of original sample values that take part in the interpolation. For example, a two-dimensional interpolation that employs values in a 4 ⁇ 4 subarray is four times as expensive as a two-dimensional interpolation that only employs values in a 2 ⁇ 2 subarray. Thus, to improve efficiency the size of the subarray of original values that contribute to each interpolation should be minimized.
  • interpolations that employ smaller subarrays of original values are less accurate than interpolations that employ larger subarrays of original.
  • the accuracy of interpolations that are obtained from small subarrays can be increased by optimizing the interpolation coefficients for a revised array of sample values that are obtained by a prefiltering operation.
  • the improvement in precision realized by this technique is significant.
  • the prefiltering step can be incorporated in prior computations at a very low cost.
  • the accuracy of finite-length interpolations can be increased by optimizing the interpolation coefficients with respect to a non-standard target frequency response. This scheme is ideally suited to the skew operations of the rotation algorithm. Further description of such interpolations as contemplated herein is provided in Appendix B.
  • each of the algorithmic improvements described herein contribute to the performance of the HABIS reconstruction procedure. However, these improvements also all have applications in other areas. For example, split-step propagations can be used to model waves of all forms, e.g., electromagnetic, seismic, ultrasonic, etc. Similarly, the efficient form of the scattering computation can also be applied to such cases.
  • the interpolation and volume rotation algorithms also have wide ranging applications that are completely independent of the reconstruction algorithm, as would be understood by a person skilled in the art.
  • Image reconstruction by HABIS is based on the scattering measurement representations given by Eq. (2) and Eq. (10). Any contributions to the scattering measurements that are not included in these representations can degrade image resolution, and may be considered noise. These contributions include conventional forms of noise such as thermal noise, crosstalk, and jitter that originate in the electronics as well include other terms that are correctly measured responses to effects for which Eq. (2) and Eq. (10) do not account. Examples of this latter form of noise are patient movement and inaccuracy in the split-step propagations of the transmitted fields. An important aspect of the HABIS design is anticipating sources of noise and finding ways to minimize the image-degrading effects of these terms. Reconstruction of high-quality images can be difficult or impossible without the noise reduction compensations described below.
  • Thermal noise from receive circuitry is inescapable.
  • the effect that this noise has on image reconstruction can be diminished if the amplitudes of the received signals can be increased without increasing the noise.
  • One way to do this is to increase the amplitude of the transmitted signals.
  • practical considerations limit driving small transducer elements with high-voltage signals.
  • high-amplitude ultrasound waves propagate nonlinearly and produce undesirable nonlinear responses.
  • reflections are amplified by transmitting ultrasound waves simultaneously from many elements that are usually concentrated by focusing in regions of interest. However, this yields a smaller set of scattering measurements that have less coherent resolution than the complete set of 10,240 ⁇ 10,240 element-to-element responses in the described imaging system.
  • the signal-to-noise ratios of HABIS scattering measurements are improved by a different method.
  • a total of 10,240 transmissions are used in each scan.
  • Each of these transmissions is a coded combinations of signals from 2,048 transmit elements.
  • the same basic pulse shape is transmitted from all of the 2,048 elements thru participate in a given transmission.
  • the sign of the pulse is inverted for a subset of the elements.
  • the subset of negated pulses changes from transmission to transmission according to a scheme that allows the received signals to be added and subtracted in combinations that isolate the responses to transmissions from each of the individual elements.
  • the purpose of this encoding and decoding of the element-to-element responses is to increase the signal-to-noise ratio of the received signals.
  • Special system characteristic have to be satisfied for this encoding to be effective because the encoding is highly sensitive to crosstalk and jitter between samples of received signals from different receive elements. Meeting the reduced tolerances for jitter and crosstalk required specially designed electronic circuitry.
  • Imaging systems that use transducer probes or small two-dimensional arrays of transducer elements that must be translated or rotated or both to acquire scattering from different orientations have relatively long scan times that introduce measurement error caused by tissue movement.
  • the HABIS scanning procedure was designed to collect a complete scan of 10,240 receive signals from each of 10,240 transmissions within a time span of about two seconds. This is essentially the smallest possible scan time for this set of transmissions because two seconds is about equal to the time required for 10,240 ultrasound transmissions to make round trip excursions through an average size breast. Numerous design challenges were met to accomplish this rapid acquisition. Signals from all 10,240 receivers had to be acquired simultaneously, so the receive channels could not be multiplexed. Thus, a separate data-acquisition channel was needed for each receiver.
  • each complete scan is comprised of nearly a terabyte (TB) of data
  • the system must include local memories to retain the acquired data as well as a high-speed data transfer system to transmit the acquired data to the high-performance computer network in a timely manner.
  • TB terabyte
  • Currently available ultrasound imaging systems employ far fewer channels and do not handle data sets of this size.
  • the HABIS inverse scattering algorithm is a coherent imaging method that resolves locations in the scattering object by forming linear combinations of residual scattering measurements that coherently sum the contributions that come from one location while incoherently summing the contributions that come from all other locations.
  • This imaging technique has higher point resolution than conventional algorithms, but can have reduced contrast resolution when the incoherent sums are appreciable.
  • incoherently summed scattering from distant reflectors is a form of noise that can degrade image quality.
  • receive time gates are used, prior to reconstruction, to isolate the scattering measurements that originate from different regions.
  • the noise reduction strategy used in HABIS is not readily applicable to other inverse scattering algorithms that perform reconstructions globally. However, time gates can be conveniently included in the HABIS reconstruction algorithm because HABIS reconstructions are partitioned into a large number of subvolumes.
  • the accuracy of the field estimates ⁇ tilde over ( ⁇ ) ⁇ m (x) and ⁇ tilde over ( ⁇ ) ⁇ n (x) also depend on the accuracy of the split-step algorithm.
  • Split-step propagations lose precision when the medium variations cause strong refraction of propagated fields, and the accumulated error that results from this refraction can be especially large when the refraction occurs in the early stages of the transmission.
  • the interface between breast tissue and the ambient, fluid is always encountered at the beginning of each transmission, and causes strong refraction when the ambient fluid is water because of the difference between the speed of sound in water and the speed of sound in tissue. For this reason, an ambient fluid other than water is desirable to minimize refraction at the breast surface.
  • the hemispheric array breast imaging system includes features that provide advantages over currently available ultrasound imaging systems, including b-scan instruments and systems that employ other forms of inverse scattering.
  • One feature is the measurement of scattering throughout a hemisphere surrounded by an array of ultrasound transducers.
  • another feature is the use of scattering measured in the hemisphere surrounded by the array to estimate scattering object detail that would come from scattering in the antipodal hemisphere, where measurements of scattering cannot be made directly.
  • the HABIS reconstruction algorithm uses scattering measured throughout an entire hemisphere surrounded by the transducer array to form an estimate of the scattering object. Additionally, the HABIS reconstruction algorithm extrapolates from the measurement hemisphere spatial frequencies that correspond to scattering in the antipodal hemisphere to obtain information equivalent to that obtained from measurement of scattering in that hemisphere.
  • the HABIS algorithm uses scattering measured in a solid angle of 2 ⁇ steradians (i.e., throughout a hemisphere encompassed by the transducer array), and uses spectral extrapolation to obtain information from scattering that cannot be measured in the antipodal hemisphere directly (i.e., throughout the antipodal solid angle of 2 ⁇ steradians corresponding to the other hemisphere).
  • the result is that spatial frequencies spanning an entire lowpass volume in the Fourier transform of the image space, a transform space known as wave space, are used by the HABIS image reconstruction algorithm to obtain the maximum theoretical amount of spatial detail contained in that volume.
  • the use of all the scattering object detail in a lowpass volume of the scattering object transform space in the HABIS reconstruction algorithm provides an advantage over other ultrasound imaging methods that only measure scattering in a plane (and so ignore out-of-plane scattering), or that only measure scattering over a relatively narrow solid angle in the forward direction (and so ignore scattering in most of the total 4 ⁇ -steradian solid angle).
  • These other methods do not obtain or use all of the measurable scattering object information. Therefore, the other methods are incapable of imaging detail associated with scattering throughout an entire solid angle of 4 ⁇ steradians.
  • HABIS Another advantageous feature of HABIS is the short data-acquisition time.
  • the data-acquisition time is about two seconds.
  • data-acquisition time which is very much shorter than in systems that rotate or otherwise move transducers to acquire data, practically eliminates motion-induced degradation of the reconstructed volume.
  • point resolution that is both high and isotropic.
  • the point resolution of HABIS is essentially equal to the lateral resolution in high-quality x-ray mammograms in which image features are typically blurred by summation of x-ray absorption along the direction of the projection.
  • Reconstructions based on inverse scattering and corresponding b-scan images have been obtained using calculated scattering by a 10-point resolution target, and by a realistic breast model derived front 200- ⁇ m resolution MRI data to illustrate the resolution and fidelity of the volumetric images produced by HABIS.
  • Each of the inverse-scattering reconstructions used scattering at the surface of the entire hemispheric transducer array, and also used an estimation of scattering object detail that would come from measurements in the opposite hemisphere where scattering cannot be directly measured.
  • This approach obtains spatial frequencies spanning an entire lowpass volume in the Fourier transform of the image space (a transform space known as wave space) to realize the maximum theoretical amount of spatial detail contained in that volume.
  • Each of the b-scans used transmission from a 64-element subtriangle and three 64-element subtriangles surrounding that central subtriangle, and used reception from the central 64 element subtriangle.
  • Use of these transmit and receive apertures takes advantage of the system architecture to allow formation of a volumetric b-scan in about one minute after a two-second interval of data collection. This b-scan has sufficient resolution to assess the quality of the acquired data for a more time-consuming volumetric reconstruction based on inverse scattering.
  • FIG. 14 Representative images of the resolution target are shown in FIG. 14 .
  • the Rayleigh-defined resolution inferred from inverse-scattering reconstructed data is 100 ⁇ m.
  • the transmit f-number was about 1.5 and the receive f-number was about 2.9.
  • the pulse spectrum used for the b-scan had a raised-cosine shape centered around 5 MHz with a ⁇ 6-dB bandwidth of 2 MHz. These transmit-receive apertures and pulse bandwidth yield an isotropic Rayleigh-defined resolution of about 700 ⁇ m.
  • a b-scan using transmission and reception throughout the hemisphere would have a lateral resolution comparable to the resolution in the reconstruction as a result of the transmit and receive effective f-numbers each being one half.
  • FIG. 15 Representative sections of a 6.4-mm3 subvolume in the breast model are shown in FIG. 15 .
  • the reconstruction was performed at a frequency of 5 MHz as in the case of the resolution target.
  • the detail evident in the reconstructed-image panel of FIG. 15 comes from the use of scattering throughout the entire surface of the hemispheric array. This scattering was first used to estimate scattering measurements that would be made by a virtual array in the opposite hemisphere and then the combined set of data was used in the reconstruction.
  • the b-scan used aberration correction.
  • the transmit f-number in the b-scan was about 3.0 and the receive f-number in the b-scan was about 6.0.
  • transmit-receive apertures yield a Rayleigh-defined lateral resolution of about 1.5 mm at the 5-MHz center frequency.
  • the pulse spectrum was the same as used for the resolution target so the axial resolution is about 700 ⁇ m as in the case of the resolution target.
  • the inverse-scattering reconstruction clearly shows the subvolume morphology with high fidelity while the b-scan mainly highlights discontinuities that are approximately perpendicular to the b-scan lines.

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